Biostatistics And Data Management Core Core Leaders: Lawrence Moulton, PhD, Jose Claudio Faulhaber, PhD, and Mauro Schechter, MD, PhD This section describes the organization and structure of the Biostatistics and Data Management core of this ICIDR Project. The main objective of this core is.to draw on and substantially enhance our existing data managing, data collecting and data analysis capabilities in order to develop a first-class Biostatistics and Data Management Center (BDMC) that will provide state-of-the-art statistical techniques and cutting-edge data management technology. In addition, the BDMC will be well prepared to exert a regional leadership role, offering training to other centers and providing other studies with statistical and data management support for their activities in clinical research in the epidemiology, treatment and prevention of TB and other tropical diseases. The existing computational infrastructure and the accumulated technical and administrative expertise will be the foundations upon which the development of the BDMC will take place. The BDMC will be actively involved in all phases of the planning, implementation, data collecting and data analysis of the projects it proposes to support and will serve as a reference center, providing training in all aspects of data management/analysis techniques to the study sites and to other institutions in Brazil. The BDMC will pursue two objectives - data management group and biostatistics. For data management, the primary objective is the implementation and supervision of all activities related to the collection, cleaning, storage and confidentiality of data generated by the projects and core activities being proposed. In addition, the group will provide computer support and training. For biostatistics, the primary objective is the development and implementation of the statistical designs and data analysis of the three research projects being proposed;the BDMC is expected to make significant contributions to the science of study design as well as methodological innovations in data analysis